Bidding with Budgets: Data-Driven Bid Algorithms in Digital Advertising

Dirk Bergemann, Alessandro Bonatti and Nick Wu

No 20263, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: In digital advertising, auctions determine the allocation of sponsored search, sponsored product, or display advertisements. The bids in these auctions for attention are largely generated by auto-bidding algorithms that are driven by platform-provided data. We analyze the equilibrium properties of a sequence of increasingly sophisticated auto-bidding algorithms. First, we consider the equilibrium bidding behavior of an individual advertiser who controls the auto-bidding algorithm through the choice of their budget. Second, we examine the interaction when all bidders use budget-controlled bidding algorithms. Finally, we derive the bidding algorithm that maximizes the platform revenue while ensuring that all advertisers continue to participate.

Keywords: Data; Advertising; Competition; Auctions (search for similar items in EconPapers)
JEL-codes: D44 D82 D83 (search for similar items in EconPapers)
Date: 2025-05
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